Hirak B.

Key Skills

Software

Internal/Proprietary Tooling

Don't disclose

Other

CVAT

Top Subject Matter

Computer Vision (object detection/annotation)

Computer Vision dataset curation and compliance

Semantic segmentation and object tracking

Top Data Types

3D Sensor

Image

Video

Text

Document

Top Task Types

Bounding Box

Classification

Object Detection

Point/Key Point

Polygon

Tracking

Segmentation

Freelancer Overview

AI Delivery Associate (Computer Vision). Core strengths include Don't disclose, Internal, and Proprietary Tooling. Education includes Bachelor of Business Administration, Inspiria Knowledge Campus (2022) and Class XII (Higher Secondary), N/A (2018). AI-training focus includes data types such as Video and Image and labeling workflows including Tracking, Bounding Box, and Segmentation.

Labeling Experience

AI Delivery Associate (Computer Vision)

CVATImageTrackingBounding Box

Performed 2D bounding box and object annotation across large-scale computer vision datasets while ensuring high-quality outputs. Conducted systematic QA/QC checks to keep annotations compliant with project guidelines. Resolved complex edge cases and ambiguous objects through active collaboration with team leads to improve workflow efficiency and delivery quality. • Managed annotation quality and consistency on dataset files • Applied object annotation standards aligned to customer requirements • Participated in iterative feedback loops to refine labeling • Handled ambiguous cases with guidance from team communication.

2024 - 2025

Data Annotator (Innodata Inc.)

CVATVideoSegmentationBounding Box

Delivered high-precision 2D bounding box annotations using the proprietary IntelLabel platform, ensuring consistent dataset quality. Labeled TinyML-related face ID and stranger detection features to support smart home security model training. Maintained data integrity and compliance with audit trails aligned to EU AI Act standards. • Managed enterprise-scale dataset labeling lineage across 100M+ images and videos. • Ensured outputs met project guidelines with QA mindset. • Coordinated annotation workflows remotely to sustain accuracy above 98%. • Supported dataset curation for downstream computer vision model development.

2022 - 2024

Data Annotator (Intellabel by Sunix AI Pvt. Ltd.)

VideoBounding Box

Lead and execute high-precision annotation workflows to support enterprise computer vision dataset development. Labeled TinyML face identification and stranger detection features for smart home security use cases. Managed data integrity and lineage for datasets exceeding 100 million images and videos while maintaining rigorous compliance and audit trails aligned with EU AI Act standards. • Produced high-precision annotations using IntelLabel • Supported face ID and stranger detection feature labeling • Ensured dataset integrity, lineage, and auditability • Followed EU AI Act-aligned dataset compliance processes.

2020

Education

Work History